The main objective of sugarcane research in the geographic valley of the Cauca River in Colombia is to improve sugarcane production in the sugar sector of the country. Different types of Remotely Piloted Aircraft Systems (RPAS) equipped with conventional and modified cameras produce images with detailed spatial and spectral information. This, together with their fast, low cost and easy handling and data collection has turned them into a success in supporting precision agriculture. The aim of this study was to evaluate the positional accuracy of orthophoto mosaics generated with RPAS imagery for sugarcane crop management and to present multiple applications derived from products that can be generated from these new technologies. Two aircrafts and two cameras were evaluated during 2015 and 2016 on positional accuracy and its products were used to estimate height (R2 = 0.73), generate furrowing lines (77.5% with an accuracy less than 0.025 m) and predict yield (R2 = 0.80). The positive results so far make these new technologies an alternative to conventional methods in precision agriculture.